Zoom (ZM)

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As of Oct 23, 2026, Kalshi and Polymarket have settled 40 word markets on Zoom’s earnings calls and other events since 2026, on 25 different words. Next call: Nov 23, 2026 (11 words listed).

Next: Earnings call ·

11 words listed · Occasion page

Who counts: Kalshi: company speakers + operator

Kalshi

Zoom: the words listed for Mon, Nov 23, how often each was said on past occasions, and the probability for this one
WordQ3’25Nov '24Q4’25Feb '25Q1’26May '25Q2’26Aug '25Q3’26year agoQ4’26Feb '26Q1’27May '26Q2’27last callTrendLast 8ScriptedAll-timeProbabilityMarket
Contact Center19 times: Contact Center, Q3’25 Nov '24, counts as said22 times: Contact Center, Q4’25 Feb '25, counts as said12 times: Contact Center, Q1’26 May '25, counts as said33 times: Contact Center, Q2’26 Aug '25, counts as said17 times: Contact Center, Q3’26 Nov '25, counts as said24 times: Contact Center, Q4’26 Feb '26, counts as said16 times: Contact Center, Q1’27 May '26, counts as said30 times: Contact Center, Q2’27 Aug '26, counts as saidsteady8/8100%8/8100%26/3087%97%n=2+tx from settlement history blended with transcripts91¢ Kalshi
Enterpriseevery call16 times: Enterprise, Q3’25 Nov '24, counts as said22 times: Enterprise, Q4’25 Feb '25, counts as said14 times: Enterprise, Q1’26 May '25, counts as said9 times: Enterprise, Q2’26 Aug '25, counts as said16 times: Enterprise, Q3’26 Nov '25, counts as said21 times: Enterprise, Q4’26 Feb '26, counts as said23 times: Enterprise, Q1’27 May '26, counts as said35 times: Enterprise, Q2’27 Aug '26, counts as saidrising8/8100%8/8100%30/30100%96%n=2+tx from settlement history blended with transcripts92¢ Kalshi
Zoom Phoneevery call4 times: Zoom Phone, Q3’25 Nov '24, counts as said3 times: Zoom Phone, Q4’25 Feb '25, counts as said6 times: Zoom Phone, Q1’26 May '25, counts as said11 times: Zoom Phone, Q2’26 Aug '25, counts as said4 times: Zoom Phone, Q3’26 Nov '25, counts as said9 times: Zoom Phone, Q4’26 Feb '26, counts as said8 times: Zoom Phone, Q1’27 May '26, counts as said9 times: Zoom Phone, Q2’27 Aug '26, counts as saidrising8/8100%8/8100%30/30100%91%n=2+tx from settlement history blended with transcripts91¢ Kalshi
AI Companion34 times: AI Companion, Q3’25 Nov '24, counts as said14 times: AI Companion, Q4’25 Feb '25, counts as said21 times: AI Companion, Q1’26 May '25, counts as said54 times: AI Companion, Q2’26 Aug '25, counts as said11 times: AI Companion, Q3’26 Nov '25, counts as said21 times: AI Companion, Q4’26 Feb '26, counts as said22 times: AI Companion, Q1’27 May '26, counts as said0 times: AI Companion, Q2’27 Aug '26falling7/888%7/888%11/3037%86%n=2+tx from settlement history blended with transcripts46¢ Kalshi
Agentic0 times: Agentic, Q3’25 Nov '249 times: Agentic, Q4’25 Feb '25, counts as said4 times: Agentic, Q1’26 May '25, counts as said6 times: Agentic, Q2’26 Aug '25, counts as said1 time: Agentic, Q3’26 Nov '25, counts as said0 times: Agentic, Q4’26 Feb '265 times: Agentic, Q1’27 May '26, counts as said6 times: Agentic, Q2’27 Aug '26, counts as saidsteady6/875%6/875%6/3020%76%n=2+tx from settlement history blended with transcripts71¢ Kalshi
Microsoft0 times: Microsoft, Q3’25 Nov '242 times: Microsoft, Q4’25 Feb '25, counts as said1 time: Microsoft, Q1’26 May '25, counts as said0 times: Microsoft, Q2’26 Aug '251 time: Microsoft, Q3’26 Nov '25, counts as said1 time: Microsoft, Q4’26 Feb '26, counts as said2 times: Microsoft, Q1’27 May '26, counts as said2 times: Microsoft, Q2’27 Aug '26, counts as saidrising6/875%4/850%13/3043%69%transcripts from the transcript model48¢ Kalshi
Google / Amazon0 times: Google / Amazon, Q3’25 Nov '2411 times: Google / Amazon, Q4’25 Feb '25, counts as said0 times: Google / Amazon, Q1’26 May '251 time: Google / Amazon, Q2’26 Aug '25, counts as said1 time: Google / Amazon, Q3’26 Nov '25, counts as said0 times: Google / Amazon, Q4’26 Feb '262 times: Google / Amazon, Q1’27 May '26, counts as said1 time: Google / Amazon, Q2’27 Aug '26, counts as saidfalling5/862%3/838%10/3033%60%transcripts from the transcript model48¢ Kalshi
OpenAI0 times: OpenAI, Q3’25 Nov '240 times: OpenAI, Q4’25 Feb '250 times: OpenAI, Q1’26 May '250 times: OpenAI, Q2’26 Aug '250 times: OpenAI, Q3’26 Nov '250 times: OpenAI, Q4’26 Feb '261 time: OpenAI, Q1’27 May '26, counts as said0 times: OpenAI, Q2’27 Aug '26steady1/812%0/80%3/3010%27%transcripts from the transcript model47¢ Kalshi
Scribe0 times: Scribe, Q3’25 Nov '240 times: Scribe, Q4’25 Feb '250 times: Scribe, Q1’26 May '250 times: Scribe, Q2’26 Aug '250 times: Scribe, Q3’26 Nov '250 times: Scribe, Q4’26 Feb '261 time: Scribe, Q1’27 May '26, counts as said0 times: Scribe, Q2’27 Aug '26steady1/812%1/812%1/303%19%n=2+tx from settlement history blended with transcripts46¢ Kalshi
Zoom Doc0 times: Zoom Doc, Q3’25 Nov '243 times: Zoom Doc, Q4’25 Feb '25, counts as said0 times: Zoom Doc, Q1’26 May '252 times: Zoom Doc, Q2’26 Aug '25, counts as said0 times: Zoom Doc, Q3’26 Nov '250 times: Zoom Doc, Q4’26 Feb '260 times: Zoom Doc, Q1’27 May '260 times: Zoom Doc, Q2’27 Aug '26falling2/825%2/825%3/3010%18%n=1+tx from settlement history blended with transcripts47¢ Kalshi
Federal0 times: Federal, Q3’25 Nov '240 times: Federal, Q4’25 Feb '251 time: Federal, Q1’26 May '25, counts as said0 times: Federal, Q2’26 Aug '250 times: Federal, Q3’26 Nov '250 times: Federal, Q4’26 Feb '260 times: Federal, Q1’27 May '260 times: Federal, Q2’27 Aug '26steady1/812%0/80%12/3040%16%n=1+tx from settlement history blended with transcripts30¢ Kalshi
  • times said on that call
  • counted as said (ring)
  • no call
  • probability next time, with n
  • Select a word or a cell for its quotes
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Market prices are mid quotes from Kalshi and Polymarket, shown for context, may be delayed by several minutes and are not a signal. Quotes as of Oct 23, 2026 00:06 UTC.

Every word

1–17 of 17, most settled first
Zoom: every word with settled markets, most settled first
WordQ3’25Nov '24Q4’25Feb '25Q1’26May '25Q2’26Aug '25Q3’26Nov '25Q4’26Feb '26Q1’27May '26Q2’27last callTrendLast 8ScriptedAll-timeProbability
My Note0 times: My Note, Q3’25 Nov '240 times: My Note, Q4’25 Feb '250 times: My Note, Q1’26 May '250 times: My Note, Q2’26 Aug '250 times: My Note, Q3’26 Nov '250 times: My Note, Q4’26 Feb '264 times: My Note, Q1’27 May '26, counts as said1 time: My Note, Q2’27 Aug '26, counts as saidrising2/825%1/812%2/307%76%n=2+tx from settlement history blended with transcripts
Workvivo15 times: Workvivo, Q3’25 Nov '24, counts as said15 times: Workvivo, Q4’25 Feb '25, counts as said5 times: Workvivo, Q1’26 May '25, counts as said9 times: Workvivo, Q2’26 Aug '25, counts as said2 times: Workvivo, Q3’26 Nov '25, counts as said4 times: Workvivo, Q4’26 Feb '26, counts as said2 times: Workvivo, Q1’27 May '26, counts as said15 times: Workvivo, Q2’27 Aug '26, counts as saidfalling8/8100%7/888%14/3047%22%n=2+tx from settlement history blended with transcripts
AI / Artificial Intelligence20+ times110 times: AI / Artificial Intelligence 20+ times, Q3’25 Nov '24, counts as said86 times: AI / Artificial Intelligence 20+ times, Q4’25 Feb '25, counts as said65 times: AI / Artificial Intelligence 20+ times, Q1’26 May '25, counts as said132 times: AI / Artificial Intelligence 20+ times, Q2’26 Aug '25, counts as said95 times: AI / Artificial Intelligence 20+ times, Q3’26 Nov '25, counts as said110 times: AI / Artificial Intelligence 20+ times, Q4’26 Feb '26, counts as said129 times: AI / Artificial Intelligence 20+ times, Q1’27 May '26, counts as said82 times: AI / Artificial Intelligence 20+ times, Q2’27 Aug '26, counts as saidsteady8/8100%8/8100%15/3050%92%n=1+tx from settlement history blended with transcripts
Camera0 times: Camera, Q3’25 Nov '240 times: Camera, Q4’25 Feb '250 times: Camera, Q1’26 May '250 times: Camera, Q2’26 Aug '250 times: Camera, Q3’26 Nov '250 times: Camera, Q4’26 Feb '261 time: Camera, Q1’27 May '26, counts as said1 time: Camera, Q2’27 Aug '26, counts as saidrising2/825%1/812%9/3030%52%n=1+tx from settlement history blended with transcripts
Churn5 times: Churn, Q3’25 Nov '24, counts as said10 times: Churn, Q4’25 Feb '25, counts as said11 times: Churn, Q1’26 May '25, counts as said7 times: Churn, Q2’26 Aug '25, counts as said5 times: Churn, Q3’26 Nov '25, counts as said6 times: Churn, Q4’26 Feb '26, counts as said14 times: Churn, Q1’27 May '26, counts as said17 times: Churn, Q2’27 Aug '26, counts as saidrising8/8100%8/8100%27/3090%95%n=1+tx from settlement history blended with transcripts
Customerevery call 25+ times90 times: Customer 25+ times, Q3’25 Nov '24, counts as said89 times: Customer 25+ times, Q4’25 Feb '25, counts as said86 times: Customer 25+ times, Q1’26 May '25, counts as said82 times: Customer 25+ times, Q2’26 Aug '25, counts as said66 times: Customer 25+ times, Q3’26 Nov '25, counts as said63 times: Customer 25+ times, Q4’26 Feb '26, counts as said98 times: Customer 25+ times, Q1’27 May '26, counts as said69 times: Customer 25+ times, Q2’27 Aug '26, counts as saidsteady8/8100%6/875%30/30100%87%n=1+tx from settlement history blended with transcripts
Latency0 times: Latency, Q3’25 Nov '240 times: Latency, Q4’25 Feb '250 times: Latency, Q1’26 May '250 times: Latency, Q2’26 Aug '250 times: Latency, Q3’26 Nov '251 time: Latency, Q4’26 Feb '26, counts as said0 times: Latency, Q1’27 May '262 times: Latency, Q2’27 Aug '26, counts as saidrising2/825%0/80%3/3010%57%n=1+tx from settlement history blended with transcripts
Quarterevery call 10+ times37 times: Quarter 10+ times, Q3’25 Nov '24, counts as said24 times: Quarter 10+ times, Q4’25 Feb '25, counts as said26 times: Quarter 10+ times, Q1’26 May '25, counts as said27 times: Quarter 10+ times, Q2’26 Aug '25, counts as said31 times: Quarter 10+ times, Q3’26 Nov '25, counts as said24 times: Quarter 10+ times, Q4’26 Feb '26, counts as said29 times: Quarter 10+ times, Q1’27 May '26, counts as said36 times: Quarter 10+ times, Q2’27 Aug '26, counts as saidsteady8/8100%4/850%30/30100%87%n=1+tx from settlement history blended with transcripts
System of Action0 times: System of Action, Q3’25 Nov '240 times: System of Action, Q4’25 Feb '251 time: System of Action, Q1’26 May '25, counts as said0 times: System of Action, Q2’26 Aug '251 time: System of Action, Q3’26 Nov '25, counts as said13 times: System of Action, Q4’26 Feb '26, counts as said9 times: System of Action, Q1’27 May '26, counts as said13 times: System of Action, Q2’27 Aug '26, counts as saidrising5/862%4/850%5/3017%91%n=1+tx from settlement history blended with transcripts
Videoevery call4 times: Video, Q3’25 Nov '24, counts as said4 times: Video, Q4’25 Feb '25, counts as said3 times: Video, Q1’26 May '25, counts as said1 time: Video, Q2’26 Aug '25, counts as said5 times: Video, Q3’26 Nov '25, counts as said4 times: Video, Q4’26 Feb '26, counts as said2 times: Video, Q1’27 May '26, counts as said3 times: Video, Q2’27 Aug '26, counts as saidsteady8/8100%7/888%30/30100%90%n=1+tx from settlement history blended with transcripts
Virtual Agent1 time: Virtual Agent, Q3’25 Nov '24, counts as said2 times: Virtual Agent, Q4’25 Feb '25, counts as said12 times: Virtual Agent, Q1’26 May '25, counts as said6 times: Virtual Agent, Q2’26 Aug '25, counts as said15 times: Virtual Agent, Q3’26 Nov '25, counts as said4 times: Virtual Agent, Q4’26 Feb '26, counts as said5 times: Virtual Agent, Q1’27 May '26, counts as said6 times: Virtual Agent, Q2’27 Aug '26, counts as saidrising8/8100%7/888%15/3050%73%n=1+tx from settlement history blended with transcripts
Workplace23 times: Workplace, Q3’25 Nov '24, counts as said16 times: Workplace, Q4’25 Feb '25, counts as said12 times: Workplace, Q1’26 May '25, counts as said12 times: Workplace, Q2’26 Aug '25, counts as said6 times: Workplace, Q3’26 Nov '25, counts as said13 times: Workplace, Q4’26 Feb '26, counts as said11 times: Workplace, Q1’27 May '26, counts as said14 times: Workplace, Q2’27 Aug '26, counts as saidfalling8/8100%8/8100%16/3053%96%n=1+tx from settlement history blended with transcripts
ZoomMate0 times: ZoomMate, Q3’25 Nov '240 times: ZoomMate, Q4’25 Feb '250 times: ZoomMate, Q1’26 May '250 times: ZoomMate, Q2’26 Aug '250 times: ZoomMate, Q3’26 Nov '250 times: ZoomMate, Q4’26 Feb '260 times: ZoomMate, Q1’27 May '266 times: ZoomMate, Q2’27 Aug '26, counts as saidrising1/812%1/812%1/303%73%n=1+tx from settlement history blended with transcripts
Anthropic0 times: Anthropic, Q3’25 Nov '240 times: Anthropic, Q4’25 Feb '251 time: Anthropic, Q1’26 May '25, counts as said0 times: Anthropic, Q2’26 Aug '250 times: Anthropic, Q3’26 Nov '254 times: Anthropic, Q4’26 Feb '26, counts as said0 times: Anthropic, Q1’27 May '260 times: Anthropic, Q2’27 Aug '26rising2/825%0/80%3/3010%18%n=1+tx from settlement history blended with transcripts
Claude0 times: Claude, Q3’25 Nov '240 times: Claude, Q4’25 Feb '250 times: Claude, Q1’26 May '250 times: Claude, Q2’26 Aug '250 times: Claude, Q3’26 Nov '250 times: Claude, Q4’26 Feb '260 times: Claude, Q1’27 May '260 times: Claude, Q2’27 Aug '26steady0/80%0/80%1/303%18%n=1+tx from settlement history blended with transcripts
Open Source0 times: Open Source, Q3’25 Nov '243 times: Open Source, Q4’25 Feb '25, counts as said0 times: Open Source, Q1’26 May '250 times: Open Source, Q2’26 Aug '250 times: Open Source, Q3’26 Nov '250 times: Open Source, Q4’26 Feb '260 times: Open Source, Q1’27 May '260 times: Open Source, Q2’27 Aug '26falling1/812%0/80%4/3013%18%n=1+tx from settlement history blended with transcripts
Oracle0 times: Oracle, Q3’25 Nov '240 times: Oracle, Q4’25 Feb '250 times: Oracle, Q1’26 May '250 times: Oracle, Q2’26 Aug '253 times: Oracle, Q3’26 Nov '25, counts as said0 times: Oracle, Q4’26 Feb '260 times: Oracle, Q1’27 May '260 times: Oracle, Q2’27 Aug '26steady1/812%1/812%2/307%18%n=1+tx from settlement history blended with transcripts
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

Appearances and settled record

latest 12

Our transcript counts matched how 26 of 26 settled words resolved (100.0%). How we check.

Recent appearances and how their listed words settled
DateAppearanceTextWordsSettledOur count agreed
Aug 25, 2026Earnings call FY27 Q2Speaker-labelled transcript2621 yes · 5 no26/26 (100%)
May 21, 2026Earnings call FY27 Q1Speaker-labelled transcript0––
Feb 26, 2026Earnings call FY26 Q4Speaker-labelled transcript0––
Nov 24, 2025Earnings call FY26 Q3Speaker-labelled transcript0––
Aug 21, 2025Earnings call FY26 Q2Speaker-labelled transcript0––
May 21, 2025Earnings call FY26 Q1Speaker-labelled transcript0––
Feb 24, 2025Earnings call FY25 Q4Speaker-labelled transcript0––
Nov 25, 2024Earnings call FY25 Q3Speaker-labelled transcript0––
Aug 21, 2024Earnings call FY25 Q2Speaker-labelled transcript0––
May 20, 2024Earnings call FY25 Q1Speaker-labelled transcript0––
Feb 26, 2024Earnings call FY24 Q4Speaker-labelled transcript0––
Nov 20, 2023Earnings call FY24 Q3Speaker-labelled transcript0––

Citeparrot.markets, “Zoom (ZM): earnings call word history”, as of Oct 23, 2026, https://parrot.markets/earnings/ZM (CC BY 4.0)

Agents: this page as TSV at /api/v1/entity/zoom · words: /api/v1/history?entity=zoom · columnar JSON in #parrot-data · llms.txt · MCP